{"id":"W4400177373","doi":"10.1080/00207543.2024.2321826","title":"The interplay between artificial intelligence, production systems, and operations management resilience","year":2024,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Resilience (materials science); Production (economics); Computer science; Production manager; Engineering; Artificial intelligence; Systems engineering; Operations management; Process management; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004684829,0.0001113846,0.0001118805,0.001136065,0.0005151017,0.002227062,0.0006360603,0.00003579092,0.00003093692],"category_scores_gemma":[0.0005870106,0.00007298596,0.00005630531,0.0008073482,0.0002871427,0.001473242,0.000299893,0.0004347102,0.0001313241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001362194,"about_ca_system_score_gemma":0.0000505372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001147831,"about_ca_topic_score_gemma":0.00005057989,"domain_scores_codex":[0.9973608,0.0000723686,0.0005887928,0.0003271805,0.001403719,0.0002471374],"domain_scores_gemma":[0.9982057,0.0001205686,0.00010722,0.0001975009,0.001347719,0.00002129704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001849813,0.0001262691,0.001805811,0.0002744654,0.0004852899,0.0001461683,0.0003895017,0.01462952,0.000642671,0.3930926,0.04838466,0.539838],"study_design_scores_gemma":[0.0001345265,0.0001173817,0.005184988,0.001289636,0.0001378177,0.0002242255,0.01965377,0.02049247,0.001577281,0.05459404,0.8962036,0.0003902367],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6764826,0.008404089,0.02738916,0.222398,0.05259036,0.002728725,0.000007166243,0.0002282652,0.009771711],"genre_scores_gemma":[0.9864674,0.001453396,0.0001591942,0.00003771021,0.008869532,0.00003383843,0.000004452767,0.0000145045,0.002959941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.847819,"threshold_uncertainty_score":0.9988087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07046898735956995,"score_gpt":0.4053773534980459,"score_spread":0.3349083661384759,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}